Computational Identification of GABA-A Receptor Ligands Targeting the Histamine Allosteric Pocket

The γ-aminobutyric acid type A (GABA-A) receptor is a key regulator of inhibitory neurotransmission in the central nervous system, and a promising target for cognitive and neurological disorders. Histamine interacts with a distinct allosteric pocket located at the β3-β3 subunit interface, providing an opportunity for the discovery of novel ligands. In the present study, an integrated in silico workflow combining ligand-based similarity analysis, ADMET filtering, molecular docking, and molecular dynamics simulations was applied to identify candidate ligands for this histamine-associated site. Docking analysis showed that ligand efficiency-related metrics discriminated active from inactive ligands more effectively than docking score alone, supporting their use during virtual screening. Three compounds were evaluated by 100 ns molecular dynamics simulations, which showed preserved receptor structural integrity and stable protein-ligand complexes. CHEMBL3236582 exhibited the most favorable dynamic profile, combining low backbone and ligand RMSD (root mean square deviation) values with the most favorable Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) binding energy estimate, whereas CHEMBL521996 maintained stable binding despite adopting an alternative binding orientation. Overall, the integrated computational workflow identified CHEMBL3236582 as the most promising candidate for experimental validation and supports further investigation of the histamine-associated allosteric pocket for the discovery of novel GABA-A receptor ligands.